Instance Constructors
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new
BacktrackingLineSearch(maxIterations: Int = 20, shrinkStep: Double = 0.5, growStep: Double = 2.1, cArmijo: Double = 1.0E-4, cWolfe: Double = 0.9, minAlpha: Double = 1.0E-10, maxAlpha: Double = 1.0E10, enforceWolfeConditions: Boolean = true, enforceStrongWolfeConditions: Boolean = true)
Type Members
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final
case class
State(alpha: Double, value: Double, deriv: Double) extends Product with Serializable
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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def
iterations(f: DiffFunction[Double], init: Double = 1.0): Iterator[State]
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def
minimize(f: DiffFunction[Double], init: Double = 1.0): Double
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def
ne(arg0: AnyRef): Boolean
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def
notify(): Unit
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def
notifyAll(): Unit
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def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from AnyRef
Inherited from Any
Implements the Backtracking Linesearch like that in LBFGS-C (which is (c) 2007-2010 Naoaki Okazaki under BSD)
Basic idea is that we need to find an alpha that is sufficiently smaller than f(0), and also possibly requiring that the slope of f decrease by the right amount (wolfe conditions)